compute_Ji_ranking: Function to compute the Ji metric ranking for publications in...

In Diderot: Bibliographic Network Analysis

Description

This function computes the Ji metric for each graph node (i.e. publication). This metric indicates how much a publication is cited simulteaneously by both corpora and is thus important for cross-fertilization between the two communities.

Usage

compute_Ji_ranking(gr, labels, infLimitYear, supLimitYear, write_to_graph=F)

Arguments

gr	Citation graph
labels	Labels (i.e. names) of the two corpora featured in the graph.
infLimitYear	Start year of the time window considered (included)
supLimitYear	End year of the time window considered (*excluded*)
write_to_graph	Flag to indicate whether to write results to the graph (i.e. save Ji values as node attributes).

Value

If write_to_graph is FALSE, returns a list of entries (authors, title, year, corpus, citations from corpus 1, citation from corpus 2, Ji) sorted by decreasing Ji. Else, returns the graph given as input to which Ji are added as node attributes.

Author(s)

Christian Vincenot ([e-mail])

See Also

build_graph, precompute_heterocitation, compute_Ji

Examples

labels<-c("Corpus1","Corpus2")

# Build a bibliographical dataset from Scopus exports
db<-create_bibliography(corpora_files=c(tempfi1,tempfi2), 
                        labels=labels, keywords=NA)


# Build graph
gr<-build_graph(db=db,small.year.mismatch=TRUE, attrs=c("Corpus","Year","Authors"), nb.cores=1)

# Compute Ji ranking
compute_Ji_ranking(gr, labels, 1990, 2018)

Diderot documentation built on April 19, 2020, 4:16 p.m.